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I don't think you're going to get that functionality until your instant pot has Wi-Fi.

Based on the numbers in the article, the fake accounts generated about $1 each on average. Based on my experience being charged fees much larger than $1 by banks, it seems like the vast majority of the accounts must have generated no fees.

I can easily see how that would happen. As a bank user, some line item in my statement with $0 in it wouldn't raise any eyebrows to me. And if I did get charged a fee, they would probably remove it if I complained. Even if my complaint got escalated, what are the odds it would be attributed to a system problem and not just some idiot who forgot he signed up for an account?

You're 100% right that "data scientist" is a fancy made-up term for people who mostly do statistics. In the same way, "software engineer" is a fancy made-up term for people who mostly do programming.

The fact that data science is basically statistics supports the argument of the guy who is saying data science and software engineering are different jobs.

If you are a software engineer and want to be a data scientist, you are free to switch careers. Or maybe work as an engineer for a startup that could use someone to do statistics on the side. But that might be a bad move with no experts around. With data science, your work product is often conclusions and advice. Those are highly susceptible to bullshit. You don't get a compiler or unit tests that tell you that you are coming to the wrong conclusion and giving bad advice. It takes experience and judgement to get that right, not just hacking on an IPython notebook and accepting what the model spits out.